1 / 10

Measuring Change

Why do we measure change?. We are interested in seeing how individuals change in response to a treatment or an interventionWe want to identify things that are correlated with changes (usually positive changes, but could also be negative)We want to see if there are group differences in response to

rayya
Download Presentation

Measuring Change

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

    1. Measuring Change Reference: Streiner, D.L, and Norman, G.R. (1995). Health measurement scales. New York: Oxford University Press.

    2. Why do we measure change? We are interested in seeing how individuals change in response to a treatment or an intervention We want to identify things that are correlated with changes (usually positive changes, but could also be negative) We want to see if there are group differences in response to a treatment

    3. Direct measurement of change Intuitively, we want to measure change directly. In other words--we want to ask the subject “Are you better now than you were before treatment?” Not a good way to determine change because research has shown that people don’t remember how they were before treatment Change scores are also called gain or difference scores

    4. Specifically: people systematically underestimate their initial condition If measured retrospectively, people estimate their initial state very similar to their current state, and not to their true initial state

    5. Reliability of Change Scores Reliability (D) = (?2D)/((?2D+?2E) Where ?2D = the systematic difference between subjects in their change score, and ?2E = the error that is associated with this estimate

    6. The reliability of the difference score is lower than the reliability of either the initial or final measurements This is shown by: R = (Rxx + Ryy - 2Rxy)/(2.0-2rxy)

    7. For example, if the reliability of the initial and final measurements are each 0.95, and there is a .80 correlation between those 2 measures, then the reliability of the change score is 0.75 As can be seen, there is a big sacrifice in reliability when change scores are used

    8. Sensitivity to Change Sensitivity to change refers to the instrument’s ability to detect the overall treatment effect This is different from the determination of individual differences, and there are several methods of estimating this In one approach, generalizability theory is used and the average difference between pre and post test scores is the variance component used in determining treatment effects (see p. 169)

    9. Problems with Change Scores Since the pre test and post test are both measured with some error (not perfect reliability), this causes the change score to have error from both tests Therefore, the error in the change score is larger than the error in either the pre test or the post test

    10. Change scores should only be used if the reliability of the pre test and post test are at least 0.50. Regression toward the mean affects the true magnitude of change scores. This can be controlled by using residualized change scores A residualized change score is the difference between the actual post test score and the predicted post test score (using regression)

More Related